Parkinson's: Predicting Risk and Progression

Two studies get at Parkinson's risk and progression

Action Points

A predictive model based on an algorithm that combined genetics, olfactory discrimination, and other factors identified Parkinson's Disease (PD) with 83% sensitivity and 90% specificity.

Three phenotypic subgroups of PD -- motor/slow progression, diffuse/malignant, and intermediate -- have different prognoses for disease progression.

Two papers published this week address fundamental questions in Parkinson's disease: can researchers predict who will develop the disease, and once it's diagnosed, how will it progress?

One, appearing in Lancet Neurology, described a predictive model based on an algorithmic combination of genetics, olfactory discrimination, and other factors that identified Parkinson's disease with 83% sensitivity and 90% specificity.

The other, published in JAMA Neurology, identified three distinct subtypes of the disease that can help clinicians determine which patients will have faster progression.

David Standaert, MD, PhD, of the University of Alabama at Birmingham, said the papers build on a fundamental change in the way experts view Parkinson's disease. Until recently, he explained, the disease was seen primarily as a motor disorder that involves tremor, slowness, and stiffness. But work in the last decade has changed that view, acknowledging the role of other symptoms such as olfactory dysfunction, sleep disorders, and cognitive impairment.

The two papers, he said, explore that new paradigm in different ways. While the JAMA paper uses non-motor features to classify different types of Parkinson's, the Lancet paper uses non-motor features to identify very early disease.

"These lead to the idea of 'pre-motor' Parkinson's disease," Standaert told MedPage Today. "Can we diagnose Parkinson's without any motor symptoms? Can we treat it before symptoms appear? Also, what about treatments targeted specifically to the non-motor aspects? These cause a lot of morbidity, especially the cognitive symptoms."

Predicting Parkinson's Risk

Patients are usually diagnosed with Parkinson's in its later stages, although the pathological processes that cause it begin years or even decades before motor symptoms become apparent. Researchers suspect that disease-modifying therapies, once developed, will be more useful if given earlier in the game.

To try to develop a means of identifying earlier stages of the disease, Andrew Singleton, PhD, of the National Institute on Aging, and colleagues developed a predictive algorithm that incorporated genetics along with select non-motor factors: olfactory discrimination, family history, age, and sex.

The genetic risk score was based on 30 variants identified in genome-wide association studies.

Singleton and colleagues found that their model correctly identified Parkinson's patients with an 83% sensitivity, and misclassified 10% of controls as having Parkinson's for a 90% specificity.

They said the test was validated in several datasets totaling 825 patients with Parkinson's and 261 controls, including the Parkinson's Disease Biomarkers Program, the Parkinson's Associated Risk Study, the 23andMe dataset, the Longitudinal and Biomarker Study in Parkinson's Disease, and the Morris Udall Parkinson's Disease Research Center of Excellence cohort.

Finally, Singleton and colleagues tested their model on patients who had imaging scans without evidence of dopaminergic deficit (SWEDD). They found that 4 of the 17 patients who their model classified as having Parkinson's disease converted to overt disease within a year, compared with only one of the 38 patients who weren't classified as having Parkinson's by their test.

"If the model can also identify individuals with prodromal or preclinical Parkinson's disease in prospective cohorts, it could facilitate identification of biomarkers and interventions," they wrote.

Standaert noted that the "most striking thing about this study ... is that the data on olfactory function is a very powerful predictor, and this is certainly a non-motor feature."

Samuel Goldman, MD, MPH, of the University of California San Francisco, warned in an accompanying editorial that if the findings were applied to the general population age 60 and up, the predictive value of a positive test would be only about 15%.

"What is most striking about these findings is how well olfactory impairment was able to distinguish between cases of Parkinson's disease and controls, and how little was added by the genetic risk score," Goldman wrote.

While it's an "exciting area of research," Goldman noted, future models need to be tested using prospective designs that longitudinally follow high-risk patients to see who actually develops the disease.

Predicting Progression

Evidence suggests that Parkinson's is heterogeneous in both clinical presentation and in prognosis, so it could be helpful to have well-characterized and distinct subtypes to better understand the underlying disease mechanisms, to predict disease course, and to design more efficient management strategies, authors of the JAMA Neurology paper wrote.

Ronald Postuma, MD, of McGill University, and colleagues performed a cluster analysis on 113 patients with idiopathic Parkinson's tracked prospectively at two movement disorder clinics in Montreal. After a mean follow-up of 4.5 years, they had data on 76 patients.

Ultimately, they found three major subtypes of the disease: mainly motor/slow progression, diffuse/malignant, and intermediate.

In patients with mainly motor/slow progression, tremor was prominent, there was a moderate prevalence of mild cognitive impairment (MCI), mild autonomic symptoms, a low prevalence of REM sleep behavior disorder (RBD), and no orthostatic hypotension. This group had the most favorable disease course with the least worsening over the study period.

Those in the diffuse/malignant group had a high prevalence of orthostatic hypotension, MCI, and RBD, and severe autonomic and motor symptoms, including gait disturbance and frequent falls. They had the most rapid and malignant progression rate of all the groups.

Finally, those in the intermediate category fell in between these two extremes. They had orthostatic hypotension but no MCI and only moderately frequent RBD. Other motor symptoms were moderate, and they had moderate progression.

Based on their findings, Postuma and colleagues recommended that clinicians should screen their Parkinson's patients for orthostatic hypotension, MCI, and RBD, since "these non-motor features identify a diffuse/malignant subgroup of patients ... for whom the most rapid progression rate could be expected."

In an accompanying editorial, Mya Caryn Schiess, MD, and Jessika Suescun, MD, of the University of Texas, agreed that the results "provide a compelling reason for all clinicians to screen patients with Parkinson's disease at initial visits for orthostatic hypotension, cognitive impairment, and sleep disorders in order to predict prognosis and tailor a management regimen."

They added that the results still need to be validated in an independent cohort and should be correlated with "imaging, genetics, blood, and cerebrospinal fluid molecular markers and other biological markers of disease progression. The multifaceted heterogeneity expressed in Parkinson's disease may actually reflect a spectrum of parkinsonian disorders instead of one highly variable disease."

Daniel Weintraub, MD, of the University of Pennsylvania, who was not involved in the study, told MedPage Today that the findings "add to the literature ... that a range of non-motor symptoms are associated with a more aggressive course in Parkinson's."

"Not sure if this has implications for treatment," he added, "unless we can show that treating these non-motor symptoms alters the course of the disease in some way."

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